Sesame CSM

Sesame CSM TTS

A 1B conversational speech model that captures natural dialogue timing, turn-taking, and backchannel responses.

Daftar untuk batas 5,000 karakter

Bungkus teks Anda dalam tag SSML untuk kendali yang tepat:

<speak><prosody rate="slow">Slow speech</prosody></speak>

Tag yang dipilih mengerti klik °C untuk memasukkan satu ke dalam teks Anda di mana hal itu terjadi:

Model ini membaca teks biasa, sehingga tag inline diabaikan. Untuk tag berbasis emosi, beralih ke model ekspresif seperti Orpheus atau Bark.

Definisikan pengucapan ubahan (kata = pelafalan):

-12 +12
0.5x 2.0x
Free with Piper, VITS, Melotts
Audio yang Anda buat akan muncul di sini. Pilih model, masukkan teks, dan klik Generate.
Hasil Audio Berhasil
0:00
Unduh Audio Unduh.srt Sambungan berakhir dalam 24 jam
Tingkatan bebas: penggunaan pribadi. Ijin komersial dari $5/mo
Buatlah ini suara Anda sendiri Kloning suara dalam 30 detik
Beritahu teman-temanmu!

Tentang Sesame CSM

Sesame CSM (Conversational Speech Model) is a 1-billion-parameter model from Sesame designed specifically for the rhythms of human conversation. Built on a Llama backbone paired with an audio codec, it models turn-taking timing, backchannel responses (the small acknowledgements people make while listening), emotional reactions, and overall conversational flow. The result reads less like read-aloud text and more like a real spoken exchange. It is a natural fit for AI assistants, chatbots, and conversational interfaces where the goal is speech that feels responsive and human. CSM is released under Apache 2.0, and access on TTS.ai requires a Hugging Face token at the model level.

Terbaik untuk: AI assistants, chatbots, conversational AI applications

Jelajahi semua Sesame CSM suara

Pada sekilas

Pengembang
Sesame
Lisensi
Apache 2.0
Tier
premium
Kecepatan
slow
Penklonan Suara
Tidak
Bahasa
English
Karakter maksimal
500

Sesame CSM suara

Speaker 0

English
Premium Neutral

Speaker 1

English
Premium Neutral

Sesame CSM TTS °F FAQ

Conversational speech. It models the natural patterns of dialogue — turn-taking timing, backchannel responses, and emotional reactions — so generated audio sounds like a real conversation rather than synthetic narration.

It is a 1-billion-parameter model built on a Llama backbone with an audio codec for waveform generation.

AI assistants, chatbots, and other conversational applications where responsive, human-sounding speech matters more than long-form narration.
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